{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pandas import Series, DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "filename = '../data/nyc_taxi_2020-07.csv'\n",
    "\n",
    "df = pd.read_csv(filename,\n",
    "           usecols=['tpep_pickup_datetime', 'passenger_count', 'trip_distance',\n",
    "                    'fare_amount','extra','mta_tax','tip_amount','tolls_amount',\n",
    "                    'improvement_surcharge','total_amount','congestion_surcharge'],\n",
    "           parse_dates=['tpep_pickup_datetime'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Beyond 1\n",
    "\n",
    "Create a bar plot, showing the average distance traveled per day of the week in July 2020. The x axis should show the name of each day."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='tpep_pickup_datetime'>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "(\n",
    "    df\n",
    "    .groupby(df['tpep_pickup_datetime'].dt.day_name())\n",
    "    ['trip_distance'].mean()\n",
    "    .plot.bar()\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Beyond 2\n",
    "\n",
    "Create a scatter plot with the taxi data from July 2020, comparing `trip_distance` with `total_amount`.  Ignore all rides in which either value was less than or equal to 0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='trip_distance', ylabel='total_amount'>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "(\n",
    "    df\n",
    "    .loc[((df['trip_distance'] > 0) &\n",
    "          (df['total_amount'] > 0) &\n",
    "          (df['trip_distance'] < 500) &\n",
    "          (df['total_amount'] < 500))]\n",
    "    .plot.scatter(x='trip_distance', y='total_amount')\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Beyond 3\n",
    "\n",
    "Create a scatter plot with the taxi data from July 2020, comparing `trip_distance` with `passenger_count`.  Ignore all rides in which `trip_distance` was less than or equal to 0, or greater than 500."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='trip_distance', ylabel='passenger_count'>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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MBZUXX3xRt9xyixISEhQfHy9JKiws1NChQ/XGG2+4ta2qqirNmDFDr776qn73u9+ZKcejOiKgNDrXIBWcPvOvTy2/I+m1bfkun1//LF+RIYH6v9lj9T8f7ldWblGTdcYlx2lFeorsoU2PfnVWZTV1mr8m22V/u+J+AgC+Z+oaFen7p9Fu3rxZ//znPyVJV1xxhSZMmOD2dmbOnKno6Gg9++yzuuGGG3TVVVfpueeea9W67XGNSkcGFU8I8LPJMKSGZobR32ZTWlKs/jT7ai9U1j7ufO0LbTtY7LK/XXE/AaArc+f72/RzVGw2myZOnKiJEyea3YTWrl2r3bt3a+fOna1qX1tbq9raWufniooK0303p7OFFEmqd1w8ZzYYhrJyi5RXXN0lTo8cLqpq9shRV9tPAMC/mbqYdv78+XrhhReazH/xxRdbfTFsYWGhHnjgAf3f//1fq19kmJGRIbvd7pwaTzuhZfkl1d4uwSOOlNa0uLyr7CcA4N9MBZW33npLaWlpTeZfc801+tvf/taqbezatUunTp3SyJEjFRAQoICAAGVmZuqFF15QQECAGhoamqyzZMkSlZeXO6fCwkIz5fuchJiucZRhQHRoi8u7yn4CAP7N1KmfkpKSJi8mlKSIiAgVFxe3ahvjx4/X3r17Xeb9/Oc/1+DBg/XII4/I39+/yTrBwcEKDg42U3Kr5C+f2ulO/7TmGpWucjokMS5c45LjLnqNSlfZTwDAv5k6opKUlKSNGzc2mb9hwwYlJia2ahvdu3fX0KFDXaawsDDFxMRo6NChZsryOZEhgXp3bprSkmKbXZ6WFKsV6V3r/Usr0lOa7G9X3E8AwPdMHVFZtGiR5s2bp6KiIt10002SpC1btujpp59u9R07VpW/fKqkjrmwNshf6uXyHJVuigoNVGRYkOLCg1VaXafdBac1IDpUNwzuoWOnz+jAd5UyDNfnqPxp9tXKK65Wfkm1Avxsqnd03eeo2EMDXfa3q+4nAOB7pm9PXrlypX7/+9/r+PHjkqSEhAQ9/vjjuvPOOz1aYEt4hD4AAJ2PO9/fpoNKo6KiIoWEhCg8PLzJsm3btmn06NHtdl0JQQUAgM6n3d/1c764uLhmQ4okTZkyRceOHWtrFwAAwEe1Oai0pI0HawAAgI9r16ACAADQFgQVAABgWQQVAABgWe0aVGw2W3tuHgAAdHFuBxXDMFRQUKCzZ8+2qi0AAIBZpoJKUlJSq14IWFlZ2epH6gMAAFzI7aDi5+en5ORklZSUtEc9AAAATqauUVm+fLkeeugh5eTkeLoeAAAAJ1OP0I+KilJNTY3q6+sVFBSkkJAQl+WlpaUeK7AlPEIfAIDOx53vb1NvT+7sb0gGAACdg6mgMnPmTE/XAQAA0ITp56gcOnRIjz76qNLT03Xq1ClJ0oYNG/TNN994rDgAAODbTAWVzMxMDRs2TDt27NDbb7+tqqoqSdJXX32lxx57zKMFAgAA32UqqCxevFi/+93vtGnTJgUFBTnn33TTTfr88889VhwAAPBtpoLK3r179eMf/7jJ/B49eqi4uLjNRQEAAEgmg0pkZKROnDjRZP6ePXvUt2/fNhcFAAAgmQwqP/3pT/XII4/o5MmTstlscjgc2rZtmx588EHdeeednq4RAAD4KFNB5YknntDgwYMVHx+vqqoqDRkyROPGjdM111yjRx991NM1AgAAH2XqybSNCgoKlJOTo6qqKqWkpCg5OdmTtV0ST6YFAKDzafcn0zbq37+/+vfv35ZNAAAAXJSpoLJo0aJm59tsNnXr1k1JSUmaNm2aoqOj21QcAADwbaZO/dx4443avXu3GhoaNGjQIEnSgQMH5O/vr8GDB2v//v2y2Wz69NNPNWTIEI8X3YhTPwAAdD7ufH+buph22rRpmjBhgo4fP65du3Zp165dOnr0qCZOnKj09HQdO3ZM48aN08KFC03tAAAAgGTyiErfvn21adOmJkdLvvnmG02aNEnHjh3T7t27NWnSpHZ9ABxHVAAA6Hza/YhKeXm580WE5ysqKlJFRYWk7x8KV1dXZ2bzAAAAktpw6ueuu+7SunXrdPToUR09elTr1q3T7NmzNX36dEnSF198ocsvv9yTtQIAAB9j6tRPVVWVFi5cqD/96U+qr6+XJAUEBGjmzJl69tlnFRYWpuzsbEnSVVdd5cl6XXDqBwCAzsed7+82PfCtqqpKhw8fliQlJiYqPDzc7KZMIagAAND5dNgD38LDwzV8+PC2bAIAAOCiTAWV6upqLV++XFu2bNGpU6fkcDhcljceZQEAAGgLU0Hl7rvvVmZmpu644w717t1bNpvN03UBAACYCyobNmzQ+++/r7S0NE/XAwAA4GTq9uSoqCje4wMAANqdqaDy29/+VkuXLlVNTY2n6wEAAHAydern6aef1qFDh9SzZ08lJCQoMDDQZfnu3btbtZ2VK1dq5cqVys/PlyRdeeWVWrp0qaZMmWKmLAAA0MWYCiqNT59tq379+mn58uVKTk6WYRhavXq1pk2bpj179ujKK6/0SB9mJSx+v8P79Jckm+Rvsyk6PFDhwYE6faZOYwZE6+EfDtaOvBJJNvnZpG9PVCo2PEhTh/eRYRg6Ulojf5vUYHy/foNhKCEmTANjw9pU0+GiKh0prXHZVnPzWpoPAIBZbXrgW3uIjo7WU089pdmzZ1+ybXs88M0bAaU9jUuO04r0FNlDAy/d+DxlNXWavyZbWblFznmpiTGy2aTPDpW4bP9306/Uo+u/cWlrtl8AQNfX7i8llKSysjL98Y9/1JIlS1RaWirp+1M+x44dM7W9hoYGrV27VtXV1UpNTTVbFi6w7WCx7l+zx+315q/J1raDrm++3n64xCWkNG5/2kvbmrQ12y8AAOczdern66+/1oQJE2S325Wfn6977rlH0dHRevvtt1VQUKA//elPrd7W3r17lZqaqrNnzyo8PFzr1q3TkCFDmm1bW1ur2tpa5+fGNzV7Slc7miJJDYahrNwi5RVXt/p0zOGiKpejI5fa/umacx7pFwCAC5k6orJo0SLNmjVLubm56tatm3P+j370I2VlZbm1rUGDBik7O1s7duzQfffdp5kzZ2rfvn3Nts3IyJDdbndO8fHxZsr3Sfkl1a1ue6TUc3dzudMvAAAXMhVUdu7cqXvvvbfJ/L59++rkyZNubSsoKEhJSUkaNWqUMjIyNGLECD3//PPNtl2yZInKy8udU2FhoZnyfVJCTOuPagyIDvVKvwAAXMhUUAkODm72tMuBAwcUFxfXpoIcDofL6Z0L+42IiHCZPCl/+VSPbs8K/G02jUuOc+v0S2JcuMYlx8m/Fa9G8LfZFBUa2KStmX4BALiQqaByyy23aNmyZTp37vtrE2w2mwoKCvTII4/otttua/V2lixZoqysLOXn52vv3r1asmSJPvnkE82YMcNMWWhGWlKsVqSnuL3eivQUpSXFusxLTYzRNZfFNNn+u3OvbdLWbL8AAJzP1O3J5eXl+o//+A99+eWXqqysVJ8+fXTy5Emlpqbqgw8+UFhY6/4VPXv2bG3ZskUnTpyQ3W7X8OHD9cgjj2jixImtWr89bk9uZIXnqHQPDlTpv56j8siUK7TjcIkMSQF+Nn1zvML5HBXp+2tBAvxsqncYzv964nkmecXVyi+pdtlWc/Namg8AwPnc+f5u03NUtm3bpq+++kpVVVUaOXKkJkyYYHZTprRnUAEAAO3Dne9vU7cnN0pLS3O+QbmsrKwtmwIAAGjC1DUq//M//6M333zT+fknP/mJYmJi1LdvX3311VceKw4AAPg2U0Hl5Zdfdj7DZNOmTdq0aZM2bNigKVOm6KGHHvJogQAAwHeZOvVz8uRJZ1B577339JOf/ESTJk1SQkKCxo4d69ECAQCA7zJ1RCUqKsr5sLWNGzc6L6I1DEMNDQ2eqw4AAPg0U0dUbr31Vv3Xf/2XkpOTVVJSoilTpkiS9uzZo6SkJI8WCAAAfJepoPLss88qISFBhYWFevLJJxUeHi5JOnHihH75y196tEAAAOC72vQcFW/jOSoAAHQ+7nx/m7pGZfXq1Xr//X8/ufXhhx9WZGSkrrnmGh05csTMJgEAAJowFVSeeOIJhYSESJK2b9+ul156SU8++aRiY2O1cOFCjxYIAAB8l6lrVAoLC50Xza5fv1633Xab5syZo7S0NN1www2erA8AAPgwU0dUwsPDVVJSIkn66KOPnC8R7Natm86cOeO56gAAgE8zdURl4sSJuvvuu5WSkqIDBw7oRz/6kSTpm2++UUJCgifrAwAAPszUEZWXXnpJqampKioq0ltvvaWYmBhJ0q5du5Senu7RAgEAgO/i9mQAANCh3Pn+NnXqp1FNTY0KCgpUV1fnMn/48OFt2SwAAIAkk0GlqKhIs2bN0saNG5tdzvt+AACAJ5i6RmXBggUqLy/Xjh07FBISoo0bN2r16tVKTk7Wu+++6+kaAQCAjzJ1RGXr1q165513NHr0aPn5+WnAgAGaOHGiIiIilJGRoalTp3q6TgAA4INMHVGprq5Wjx49JElRUVEqKiqSJA0bNky7d+/2XHUAAMCnmQoqgwYN0v79+yVJI0aM0CuvvKJjx47p5ZdfVu/evT1aIAAA8F2mTv088MADOnHihCTpscce0w9/+EO98cYbCgoK0urVqz1aIAAA8F1tfo6KYRg6c+aM/vnPf6p///6KjY31VG2XxHNUAADofNz5/jZ16keSXnvtNQ0dOlTdunVTVFSU7rzzTq1fv97s5gAAAJowdepn6dKleuaZZ3T//fcrNTVVkrR9+3YtXLhQBQUFWrZsmUeLBAAAvsnUqZ+4uDi98MILTd7rs2bNGt1///0qLi72WIEt4dQPAACdT7uf+jl37pxGjx7dZP6oUaNUX19vZpMAAABNmAoqd9xxh1auXNlk/h/+8AfNmDGjzUUBAABIbXgp4WuvvaaPPvpIP/jBDyRJO3bsUEFBge68804tWrTI2e6ZZ55pe5UAAMAnmQoqOTk5GjlypCTp0KFDkqTY2FjFxsYqJyfH2c5ms3mgRAAA4KtMBZWPP/7Y03UAAAA0Yfo5KgAAAO2NoAIAACyLoAIAACyLoAIAACyLoAIAACyLoAIAACzLq0ElIyNDY8aMUffu3dWjRw9Nnz5d+/fv92ZJAADAQkw/mdYTMjMzNXfuXI0ZM0b19fX67//+b02aNEn79u1TWFiYN0tTwuL3vdp/Iz+bFB0aqLjuwSqtrlNVbYMchqHY8CDFhgdLkmLDg7X3WLlKq2vVPypMS2+5UtmFp1VaXachve06WXFWe4+VqXtwgH6QGKMGQ7JJGpsYo4Gx//45Hy6q0pHSGiXEhDnnNzfvQq1pg+bxswOAlpl6e3J7KSoqUo8ePZSZmalx48Zdsn17vD3ZKgGlo1xzWYyW3zpcj67PUVZukXN+amKMbDbps0MlznnjkuO0Ij1F9tBASVJZTZ3mr8l2We/CNmgePzsAvqzd357cXsrLyyVJ0dHRXq7Ed3x2qETTXvpU2w4Wu8zffrjEJaRI0raDxbp/zR7n5/lrspusd2EbNI+fHQC0jldP/ZzP4XBowYIFSktL09ChQ5ttU1tbq9raWufniooKj9bga0dTGp2uOdeqdg2GoazcIuUVV8v4159basOpjOYdLqriZwcArWSZIypz585VTk6O1q5de9E2GRkZstvtzik+Pr4DK0Sj/JJqHSmtuWQbNI+fHQC0niWCyrx58/Tee+/p448/Vr9+/S7absmSJSovL3dOhYWFHVglGiXEhGlAdOgl26B5/OwAoPW8GlQMw9C8efO0bt06bd26VQMHDmyxfXBwsCIiIlwmT8pfPtWj2+ssokID5W+zXbKdv82mcclxGhgbpsS4cI1Ljmuy3vlt0Dx+dgDQel4NKnPnztUbb7yhP//5z+revbtOnjypkydP6syZM94sy6dcc1mM3p17rdKSYl3mpybG6JrLYlzmpSXFakV6ivPzivSUJutd2AbN42cHAK3j1duTbRf5V/zrr7+uWbNmXXL99rg9uZFVLqz1s0kxoYGK695NpTW1qjz7/XNU4sKDFRMeLJsMxYZ3U86xMhX/6zkqj027Ul8Vlqm4qlZX9vnXc1SOlik8OECpl8Wq3mE0+xyVvOJq5ZdUuzzTo7l5F2pNGzSPnx0AX+TO97elnqPirvYMKgAAoH102ueoAAAAnI+gAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALIugAgAALMurQSUrK0s333yz+vTpI5vNpvXr13uzHAAAYDEB3uy8urpaI0aM0F133aVbb73Vm6U0kbD4fW+X0K6iQgI0MDZcp6rOqvpsvaLDghQREqiC0ho5HIb62LspIjRIV/axKyIkQPnF1bLZbKo4c06SNCI+UlOH99HA2DBl7j+lj/ef0vGyM6o6W6/BvSN0w6AeajAMJcSEyTAMHSmtUUJMmAbGhrnUcbioqsmyw0VV2pFXIsmmHyTGqKCkWtlHyzSyf5T6Roa4tG9c398mHSs7K5ukPpHddKzsjCSb+kaG6FhZjXNbrelfkjL3n3L2eV1yXJO2Le1Ta1ysX7Sf5sa0tTw5Xow9OhMr/L7aDMMwvNLzBWw2m9atW6fp06e3ep2KigrZ7XaVl5crIiLCI3V09YDiaX6SHG60H5ccpxXpKTJkaP6abGXlFjmXpSbGqMHh0Bf5p1u1rajQQJ2uOedWvamJMXr5Z6Oa7X9ccpwenny57vjfL1y2aw8J0KCeEfoiv7TFfbKHBl6y/7Kaumb7be36cN+RkmpNf2mby5hGhQbq3bnXKj4mtMV1PTlejD06k/b+fXXn+5ugcgGCSvvyt9mUlhQrSdp2sFgNXvj1G/evf01f2L+/zSabTap3uFdT4z79afbVl2x752tfNNtva9eH+1KWfdRsoI0KDdSepZNaXNeT48XYozNp799Xd76/O9XFtLW1taqoqHCZPImQ0v4aDENZuUXKyi3ySkiRdNH+GwzD7ZDSuF5WbpHyiqtbbHe4qOqi/bZmfbgvc/+pix51O11zTv8471+LF/LkeDH26Eys9vvaqYJKRkaG7Ha7c4qPj/d2SYBTfknLf3mPlNa0aX24L/toWYvLdxdc/DSjJ8eLsUdnYrXf104VVJYsWaLy8nLnVFhY6O2SAKeEmJYvNBsQ3fL1EJdaH+67ql9ki8tH9o+66DJPjhdjj87Ear+vnSqoBAcHKyIiwmXypPzlUz26PTTlb7NpXHKcxiXHyd9m80oNF+vf32ZTgJ/7NTXu06WuiE+MC79ov61ZH+67flAPRV3kwr+o0MAW7/7x5Hgx9uhMrPb76tWgUlVVpezsbGVnZ0uS8vLylJ2drYKCAm+WBTe4+wuUlhSrFekpWpGe4ryotlFqYoyuTohu9bYu9gXUktTEmIv2n5YUq3fnpjXZrj0koMW6GvepNS7Wb2vXh/venXttkzFtvOvnUjw5Xow9OhMr/b569a6fTz75RDfeeGOT+TNnztSqVasuuX573PXTqKtfWBsVEqDE2HCdqqpV1dlzig4Llj0kUAWl1WpwGOobGaLuIYG6so9dkaGBOlxULZtNqjxTL8NmaES/fz9H5R+5Rdry7Xc6UXZWlWfrNbh3d904uIfqHYbzEGF+SXWz9+HnFVc3WZZXXK0dh0tkSPpBYoyOnq7R7oLTGtk/Sv2iQl3aN64f4GfT0dNnZJPUNypEx06fkSGp33l/bu45Ks31L0n/yC1y9tn4r+7z27a0T61xsX7Rfpob09by5Hgx9uhM2uv3tVPenmxGewYVAADQPrrs7ckAAMC3EFQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlEVQAAIBlWSKovPTSS0pISFC3bt00duxYffHFF94uCQAAWECAtwt48803tWjRIr388ssaO3asnnvuOU2ePFn79+9Xjx49vFZXwuL3O6Qff0lhwf6yhwaqZ3g3fVdVq3MNDUqKC1dSzwiNv6KH+kaG6EhpjRJiwlRQUq3so2Ua2T/KZf7A2DAdLqpq8bM7zK7blj7N6Oj+vM1X9tdX9hPApdkMwzC8WcDYsWM1ZswYvfjii5Ikh8Oh+Ph43X///Vq8eHGL61ZUVMhut6u8vFwREREeqaejAoqnRYUG6nTNuYt+HpccpxXpKbKHBra4nbKaOs1fk62s3CK31jW7nlkd3Z+3+cr++sp+Ar7One9vr576qaur065duzRhwgTnPD8/P02YMEHbt2/3YmWdz/mhpLnP2w4W6/41ey65nflrsrXtYLHb65pdz6yO7s/bfGV/fWU/AbSeV4NKcXGxGhoa1LNnT5f5PXv21MmTJ5u0r62tVUVFhcvkSZ31aEprNBiGsnKLlFdcfdE2h4uqlJVbpIYLDrJdal2z65nV0f15m6/sr6/sJwD3WOJi2tbKyMiQ3W53TvHx8d4uqdPJL7n4/+yPlNaYWtfsemZ1dH/e5iv76yv7CcA9Xg0qsbGx8vf313fffecy/7vvvlOvXr2atF+yZInKy8udU2FhYUeV2mUkxFz8wsQB0aGm1jW7nlkd3Z+3+cr++sp+AnCPV4NKUFCQRo0apS1btjjnORwObdmyRampqU3aBwcHKyIiwmXypPzlUz26PSvxt9k0LjmuxTsoEuPCNS45Tv42m1vrml3PrI7uz9t8ZX99ZT8BuMfrp34WLVqkV199VatXr9a3336r++67T9XV1fr5z3/u7dI6lagL7oi48HNaUqxWpKdccjsr0lOUlhTr9rpm1zOro/vzNl/ZX1/ZTwCt5/XbkyXpxRdf1FNPPaWTJ0/qqquu0gsvvKCxY8decr32uD25kVeeo9K9m76rbHyOSncl9eyu8Vf0UL+oUOWXVCshJkxHT9dod8Fpjewf5TJ/YGyY8oqrW/zsDrPrtqVPMzq6P2/zlf31lf0EfJU739+WCCpmtWdQAQAA7aPTPEcFAACgJQQVAABgWQQVAABgWQQVAABgWQQVAABgWQQVAABgWQQVAABgWQQVAABgWQQVAABgWQQVAABgWQHeLqAtGp/+X1FR4eVKAABAazV+b7fmLT6dOqhUVlZKkuLj471cCQAAcFdlZaXsdnuLbTr1SwkdDoeOHz+u7t27y2azeXTbFRUVio+PV2FhIS887CQYs86F8ep8GLPOx6pjZhiGKisr1adPH/n5tXwVSqc+ouLn56d+/fq1ax8RERGWGlxcGmPWuTBenQ9j1vlYccwudSSlERfTAgAAyyKoAAAAyyKoXERwcLAee+wxBQcHe7sUtBJj1rkwXp0PY9b5dIUx69QX0wIAgK6NIyoAAMCyCCoAAMCyCCoAAMCyCCrNeOmll5SQkKBu3bpp7Nix+uKLL7xdks/KysrSzTffrD59+shms2n9+vUuyw3D0NKlS9W7d2+FhIRowoQJys3NdWlTWlqqGTNmKCIiQpGRkZo9e7aqqqo6cC98R0ZGhsaMGaPu3burR48emj59uvbv3+/S5uzZs5o7d65iYmIUHh6u2267Td99951Lm4KCAk2dOlWhoaHq0aOHHnroIdXX13fkrviMlStXavjw4c7nbKSmpmrDhg3O5YyX9S1fvlw2m00LFixwzutK40ZQucCbb76pRYsW6bHHHtPu3bs1YsQITZ48WadOnfJ2aT6purpaI0aM0EsvvdTs8ieffFIvvPCCXn75Ze3YsUNhYWGaPHmyzp4962wzY8YMffPNN9q0aZPee+89ZWVlac6cOR21Cz4lMzNTc+fO1eeff65Nmzbp3LlzmjRpkqqrq51tFi5cqL///e/661//qszMTB0/fly33nqrc3lDQ4OmTp2quro6ffbZZ1q9erVWrVqlpUuXemOXurx+/fpp+fLl2rVrl7788kvddNNNmjZtmr755htJjJfV7dy5U6+88oqGDx/uMr9LjZsBF1dffbUxd+5c5+eGhgajT58+RkZGhhergmEYhiRj3bp1zs8Oh8Po1auX8dRTTznnlZWVGcHBwcaaNWsMwzCMffv2GZKMnTt3Otts2LDBsNlsxrFjxzqsdl916tQpQ5KRmZlpGMb34xMYGGj89a9/dbb59ttvDUnG9u3bDcMwjA8++MDw8/MzTp486WyzcuVKIyIiwqitre3YHfBRUVFRxh//+EfGy+IqKyuN5ORkY9OmTcb1119vPPDAA4ZhdL2/ZxxROU9dXZ127dqlCRMmOOf5+flpwoQJ2r59uxcrQ3Py8vJ08uRJl/Gy2+0aO3asc7y2b9+uyMhIjR492tlmwoQJ8vPz044dOzq8Zl9TXl4uSYqOjpYk7dq1S+fOnXMZs8GDB6t///4uYzZs2DD17NnT2Wby5MmqqKhw/isf7aOhoUFr165VdXW1UlNTGS+Lmzt3rqZOneoyPlLX+3vWqd/142nFxcVqaGhwGThJ6tmzp/75z396qSpczMmTJyWp2fFqXHby5En16NHDZXlAQICio6OdbdA+HA6HFixYoLS0NA0dOlTS9+MRFBSkyMhIl7YXjllzY9q4DJ63d+9epaam6uzZswoPD9e6des0ZMgQZWdnM14WtXbtWu3evVs7d+5ssqyr/T0jqABoF3PnzlVOTo4+/fRTb5eCSxg0aJCys7NVXl6uv/3tb5o5c6YyMzO9XRYuorCwUA888IA2bdqkbt26ebucdsepn/PExsbK39+/yZXR3333nXr16uWlqnAxjWPS0nj16tWryYXQ9fX1Ki0tZUzb0bx58/Tee+/p448/dnnDea9evVRXV6eysjKX9heOWXNj2rgMnhcUFKSkpCSNGjVKGRkZGjFihJ5//nnGy6J27dqlU6dOaeTIkQoICFBAQIAyMzP1wgsvKCAgQD179uxS40ZQOU9QUJBGjRqlLVu2OOc5HA5t2bJFqampXqwMzRk4cKB69erlMl4VFRXasWOHc7xSU1NVVlamXbt2Odts3bpVDodDY8eO7fCauzrDMDRv3jytW7dOW7du1cCBA12Wjxo1SoGBgS5jtn//fhUUFLiM2d69e10C5qZNmxQREaEhQ4Z0zI74OIfDodraWsbLosaPH6+9e/cqOzvbOY0ePVozZsxw/rlLjZu3r+a1mrVr1xrBwcHGqlWrjH379hlz5swxIiMjXa6MRseprKw09uzZY+zZs8eQZDzzzDPGnj17jCNHjhiGYRjLly83IiMjjXfeecf4+uuvjWnTphkDBw40zpw549zGD3/4QyMlJcXYsWOH8emnnxrJyclGenq6t3apS7vvvvsMu91ufPLJJ8aJEyecU01NjbPNL37xC6N///7G1q1bjS+//NJITU01UlNTncvr6+uNoUOHGpMmTTKys7ONjRs3GnFxccaSJUu8sUtd3uLFi43MzEwjLy/P+Prrr43FixcbNpvN+OijjwzDYLw6i/Pv+jGMrjVuBJVmrFixwujfv78RFBRkXH311cbnn3/u7ZJ81scff2xIajLNnDnTMIzvb1H+9a9/bfTs2dMIDg42xo8fb+zfv99lGyUlJUZ6eroRHh5uREREGD//+c+NyspKL+xN19fcWEkyXn/9dWebM2fOGL/85S+NqKgoIzQ01Pjxj39snDhxwmU7+fn5xpQpU4yQkBAjNjbW+NWvfmWcO3eug/fGN9x1113GgAEDjKCgICMuLs4YP368M6QYBuPVWVwYVLrSuPH2ZAAAYFlcowIAACyLoAIAACyLoAIAACyLoAIAACyLoAIAACyLoAIAACyLoAIAACyLoAIAACyLoAKgWY8//riuuuqqdu3jhhtu0IIFC5yfExIS9Nxzz7VrnwA6F4IK4GMuDAcX8+CDD7q81Kwj7Ny5U3PmzGlVW0IN4BsCvF0AAGsxDEMNDQ0KDw9XeHh4h/YdFxfXof0BsD6OqAA+ZNasWcrMzNTzzz8vm80mm82mVatWyWazacOGDRo1apSCg4P16aefNjn1M2vWLE2fPl2/+c1vFBcXp4iICP3iF79QXV1dq/qurq7WnXfeqfDwcPXu3VtPP/10kzbnHyUxDEOPP/64+vfvr+DgYPXp00fz58+X9P1RoSNHjmjhwoXO/ZCkkpISpaenq2/fvgoNDdWwYcO0Zs0alz5uuOEGzZ8/Xw8//LCio6PVq1cvPf744y5tysrKdO+996pnz57q1q2bhg4dqvfee8+5/NNPP9V1112nkJAQxcfHa/78+aqurm7VzwGAewgqgA95/vnnlZqaqnvuuUcnTpzQiRMnFB8fL0lavHixli9frm+//VbDhw9vdv0tW7bo22+/1SeffKI1a9bo7bff1m9+85tW9f3QQw8pMzNT77zzjj766CN98skn2r1790Xbv/XWW3r22Wf1yiuvKDc3V+vXr9ewYcMkSW+//bb69eunZcuWOfdDks6ePatRo0bp/fffV05OjubMmaM77rhDX3zxhcu2V69erbCwMO3YsUNPPvmkli1bpk2bNkmSHA6HpkyZom3btumNN97Qvn37tHz5cvn7+0uSDh06pB/+8Ie67bbb9PXXX+vNN9/Up59+qnnz5rXq5wDATd59eTOAjnbh6+A//vhjQ5Kxfv16l3aPPfaYMWLECOfnmTNnGtHR0UZ1dbVz3sqVK43w8HCjoaGhxT4rKyuNoKAg4y9/+YtzXklJiRESEuJSy4ABA4xnn33WMAzDePrpp43LL7/cqKura3ab57dtydSpU41f/epXzs/XX3+9ce2117q0GTNmjPHII48YhmEYH374oeHn52fs37+/2e3Nnj3bmDNnjsu8f/zjH4afn59x5syZS9YDwD0cUQEgSRo9evQl24wYMUKhoaHOz6mpqaqqqlJhYWGL6x06dEh1dXUaO3asc150dLQGDRp00XVuv/12nTlzRomJibrnnnu0bt061dfXt9hPQ0ODfvvb32rYsGGKjo5WeHi4PvzwQxUUFLi0u/CIUe/evXXq1ClJUnZ2tvr166fLL7+82T6++uorrVq1ynkNT3h4uCZPniyHw6G8vLwW6wPgPi6mBSBJCgsL83YJLuLj47V//35t3rxZmzZt0i9/+Us99dRTyszMVGBgYLPrPPXUU3r++ef13HPPadiwYQoLC9OCBQuaXEdz4fo2m00Oh0OSFBIS0mJdVVVVuvfee53Xy5yvf//+7uwigFYgqAA+JigoSA0NDabW/eqrr3TmzBnnl/nnn3+u8PBw53UuF3PZZZcpMDBQO3bscH6Znz59WgcOHND1119/0fVCQkJ088036+abb9bcuXM1ePBg7d27VyNHjmx2P7Zt26Zp06bpZz/7maTvrzc5cOCAhgwZ0up9HD58uI4ePaoDBw40e1Rl5MiR2rdvn5KSklq9TQDmceoH8DEJCQnasWOH8vPzVVxc7DyS0Bp1dXWaPXu29u3bpw8++ECPPfaY5s2bJz+/lv9XEh4ertmzZ+uhhx7S1q1blZOTo1mzZrW43qpVq/Taa68pJydHhw8f1htvvKGQkBANGDDAuR9ZWVk6duyYiouLJUnJycnatGmTPvvsM3377be699579d1337V6/yTp+uuv17hx43Tbbbdp06ZNysvL04YNG7Rx40ZJ0iOPPKLPPvtM8+bNU3Z2tnJzc/XOO+9wMS3QTggqgI958MEH5e/vryFDhiguLq7J9RstGT9+vJKTkzVu3Dj953/+p2655ZYmt/ZezFNPPaXrrrtON998syZMmKBrr71Wo0aNumj7yMhIvfrqq0pLS9Pw4cO1efNm/f3vf1dMTIwkadmyZcrPz9dll13mfP7Ko48+qpEjR2ry5Mm64YYb1KtXL02fPr3V+9forbfe0pgxY5Senq4hQ4bo4Ycfdh69GT58uDIzM3XgwAFdd911SklJ0dKlS9WnTx+3+wFwaTbDMAxvFwHA+mbNmqWysjKtX7/e26UA8CEcUQEAAJZFUAHQZgUFBS636144uXN6CQDOx6kfAG1WX1+v/Pz8iy5PSEhQQAA3GQJwH0EFAABYFqd+AACAZRFUAACAZRFUAACAZRFUAACAZRFUAACAZRFUAACAZRFUAACAZRFUAACAZf0/Q5IRBJbsTh4AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "(\n",
    "    df\n",
    "    .loc[((df['trip_distance'] > 0) &\n",
    "          (df['trip_distance'] < 500))]\n",
    "    .plot.scatter(x='trip_distance', y='passenger_count')\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
